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Level 1 · Entry Foundations

Goal: understand every moving part of a data pipeline — Python and SQL for data work, ETL, data modeling, file formats, batch processing, orchestration concepts, and data quality — and ship a working ETL pipeline built from those parts in plain Python.

Modules

  1. What Is Data Engineering?
  2. Python for Data Engineering
  3. SQL for Data Engineers
  4. ETL Fundamentals
  5. Data Modeling Basics
  6. Working with File Formats
  7. Batch Processing Basics
  8. Intro to Orchestration
  9. Data Quality & Validation
  10. Project — Build a Simple ETL Pipeline

By the end of this level you'll be able to take a folder of raw files, model them into a clean schema, load them into a database with validation, and recognize (and fix) the most common ways real-world pipelines break — schema drift, duplicate loads, and late-arriving data.

Setup for this level

pip install pandas
Everything else — sqlite3, csv, json, pathlib — is in the Python standard library. No cloud account, no API key, no server to install. All code on this level runs fully offline.